Biography
Abstract
The economic growth of the State of Pernambuco above the national average in recent years can be attributed to investments in the sectors of construction and industry, which has its main pillars in the Industrial and Port Complex Governor Eraldo Leite Gueiros Suape (CIPS) and the tourist pole. To ensure the continuity of the development of this region over the next few years, the water supply is ensured by Suape System and already own of the Utinga (10,270,000 m3) and Bita (2,7000,000 m3) dams, will win a big boost with the construction of the Engenho Maranhão (50,000,000 m³) dam on the river Ipojuca. The Ipojuca river receives untreated sewage from several densely populated municipalities of its watershed, and crosses the sugar cane area where use fertilizers and pesticides, contributing to the degradation of this river. Therefore, to investigate the changes in the quality of water from dams with Bita and Utinga technical principal components analysis (PCA) and Multilayer Perceptron artificial neural networks (MLP ANN) was applied, and compared with the resolution of the National Council for the Environment (CONAMA) 357/05. The study involved collections of samples carried out in the period from February 2007 to March 2013. Of the water samples used, it was observed that 78.5% were at odds with the limits of Resolution CONAMA 357/2005 for Class 2 fresh water. The parameters presented in violation of the resolution were hydrogen potential dissolved oxygen, biochemical oxygen demand, total phosphorus, turbidity, total solids and thermotolerant coliforms. The results of PCA the first four components explain 65.92% of the total variation of the data. The first component (PC1) explained 26.5% of the data variance and the most important variables for water quality were the OD (0.80), BOD (-0.78), thermotolerant coliforms (-0.78) and ST (- 0.56). The MLPANN that showed the best performance was with 11 neurons in the hidden layer, hyperbolic tangent function and softmax function for the output layer, obtaining an average of 89.7% of global successes and 83.6% of correct answers in the test. The performance of the MLP ANN 9-11-5 model, the most significant input parameters in the identification of water quality were the total phosphorus, thermotolerant coliforms and dissolved oxygen concentrations. The result shows a tendency to water quality degradation from dams due to the presence of microorganisms, salts and nutrients responsible for the eutrophication process, which is configured by the greatest concentration of the total phosphorus and thermotolerant coliforms, and lower pH and DO, probably due to occurrence of effluent disposal of industrial, domestic and Agroin-sugarcane industry.
Biography
Abstract
The study of the pollution of water matrices is increasing and is continuous between the members of the scientific community and because of which drinking and water fit for human consumption considerably decreases each year. Identifying and quantifying the different classes of pollutants is extremely necessary, especially when we see that among the most identified compounds are drugs. Use of contaminants is increased by the world\'s population without specific control to its discharge to the environment. Effluents from different origin were collected and analyzed for the presence of four drugs studied before and after application of AOP, by analysis via liquid chromatography high efficiency (HPLC). To ensure data reliability methodology, validation was performed using HPLC as required by competent bodies (ANVISA and INMETRO). The use of advanced oxidation processes (AOP) are the object of study and as an alternative capable of promoting the degradation of pollutants from contaminated means. This study aims to assess, identify and quantify the drugs, aspirin, diclofenac, dipirone and paracetamol in different effluents from wastewater treatment plants for use of different AOP. Total organic carbon analyzes were performed to verify the conversion of organic after treatment. Among the drugs studied, three of them were detected in effluents at concentrations ranging from 0.29 mgL-1 to 3.96 mgL-1. The best results were obtained using a bench reactor employing like Photo-Fenton process which observed degradation of drug from 71.9% to 100.0%, and a conversion of organic matter equal to 66.5%.